Overview

Dataset statistics

Number of variables20
Number of observations240
Missing cells0
Missing cells (%)0.0%
Duplicate rows24
Duplicate rows (%)10.0%
Total size in memory37.6 KiB
Average record size in memory160.5 B

Variable types

NUM20

Reproduction

Analysis started2020-08-25 00:00:26.768113
Analysis finished2020-08-25 00:01:21.266521
Duration54.5 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

Dataset has 24 (10.0%) duplicate rows Duplicates
absorbance_43 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_19 is highly correlated with absorbance_43 and 15 other fieldsHigh correlation
absorbance_37 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_77 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_54 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_91 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_57 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
principal_component_22 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_5 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_28 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_45 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_96 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_20 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_78 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_11 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
principal_component_1 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
absorbance_12 is highly correlated with absorbance_19 and 15 other fieldsHigh correlation
target is highly correlated with moistureHigh correlation
moisture is highly correlated with targetHigh correlation

Variables

absorbance_19
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count215
Unique (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.900202876329422
Minimum2.0709199905395512
Maximum4.503210067749023
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:21.314688image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.070919991
5-th percentile2.25751996
Q12.566262484
median2.816080093
Q33.164000034
95-th percentile3.753278911
Maximum4.503210068
Range2.432290077
Interquartile range (IQR)0.5977375507

Descriptive statistics

Standard deviation0.4627075494
Coefficient of variation (CV)0.1595431662
Kurtosis0.5609614523
Mean2.900202876
Median Absolute Deviation (MAD)0.2894300222
Skewness0.7878484167
Sum696.0486903
Variance0.2140982763
2020-08-25T00:01:21.416259image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.49798011820.8%
 
2.24825000820.8%
 
3.01978993420.8%
 
2.54465007820.8%
 
3.63309001920.8%
 
2.2575199620.8%
 
2.39175009720.8%
 
2.26005005820.8%
 
2.31364989320.8%
 
3.02016997320.8%
 
3.28749990520.8%
 
2.20351004620.8%
 
2.72415995620.8%
 
2.68094992620.8%
 
2.1605799220.8%
 
4.0206499120.8%
 
3.22648000720.8%
 
2.73572993320.8%
 
2.96037006420.8%
 
2.37179994620.8%
 
2.81221008320.8%
 
2.76377010320.8%
 
2.62988996520.8%
 
3.47931003620.8%
 
2.43570995320.8%
 
Other values (190)19079.2%
 
ValueCountFrequency (%) 
2.07091999110.4%
 
2.1605799220.8%
 
2.19210004810.4%
 
2.20054006610.4%
 
2.20351004620.8%
 
2.22414994210.4%
 
2.24825000820.8%
 
2.25145006210.4%
 
2.2575199620.8%
 
2.25763988510.4%
 
ValueCountFrequency (%) 
4.50321006810.4%
 
4.45195007310.4%
 
4.27223014810.4%
 
4.15043020210.4%
 
4.0206499120.8%
 
3.98787999210.4%
 
3.94226002710.4%
 
3.83579993210.4%
 
3.81364989310.4%
 
3.81289005310.4%
 

absorbance_43
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1770017911990482
Minimum2.201280117034912
Maximum5.1852898597717285
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:21.528636image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.201280117
5-th percentile2.413398516
Q12.782559931
median3.075719953
Q33.539352536
95-th percentile4.166873169
Maximum5.18528986
Range2.984009743
Interquartile range (IQR)0.7567926049

Descriptive statistics

Standard deviation0.5535418727
Coefficient of variation (CV)0.1742340449
Kurtosis0.6729464798
Mean3.177001791
Median Absolute Deviation (MAD)0.3609399796
Skewness0.8076085223
Sum762.4804299
Variance0.3064086048
2020-08-25T00:01:21.632370image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.22266006520.8%
 
2.41223001520.8%
 
2.88613009520.8%
 
4.35464000720.8%
 
2.4752900620.8%
 
2.78973007220.8%
 
2.69502997420.8%
 
2.35316991820.8%
 
2.39384007520.8%
 
3.62929010420.8%
 
3.52872991620.8%
 
2.54257011420.8%
 
3.15219998420.8%
 
3.54349994720.8%
 
3.06295990920.8%
 
3.13416004220.8%
 
2.41346001620.8%
 
3.89436006520.8%
 
2.29710006720.8%
 
2.59812998820.8%
 
2.83390998820.8%
 
3.98446989120.8%
 
3.71669006320.8%
 
2.60587000820.8%
 
2.64898991610.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.20128011710.4%
 
2.29710006720.8%
 
2.35316991820.8%
 
2.36268997210.4%
 
2.37213993110.4%
 
2.39227008810.4%
 
2.39384007520.8%
 
2.41223001520.8%
 
2.41346001620.8%
 
2.41860008210.4%
 
ValueCountFrequency (%) 
5.1852898610.4%
 
5.01484012610.4%
 
4.78667020810.4%
 
4.70336008110.4%
 
4.64074993110.4%
 
4.64022016510.4%
 
4.40012979510.4%
 
4.35464000720.8%
 
4.32307004910.4%
 
4.21054983110.4%
 

absorbance_37
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0805174628893535
Minimum2.119080066680908
Maximum5.0487799644470215
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:21.745069image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.119080067
5-th percentile2.334641504
Q12.694422483
median2.977229953
Q33.440812469
95-th percentile4.012723875
Maximum5.048779964
Range2.929699898
Interquartile range (IQR)0.7463899851

Descriptive statistics

Standard deviation0.5404062887
Coefficient of variation (CV)0.1754271142
Kurtosis0.6705578814
Mean3.080517463
Median Absolute Deviation (MAD)0.3492400646
Skewness0.7941846529
Sum739.3241911
Variance0.2920389568
2020-08-25T00:01:21.850465image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.76919007320.8%
 
3.88536000320.8%
 
3.03391003620.8%
 
2.32950997420.8%
 
2.33162999220.8%
 
2.3372099420.8%
 
2.76245999320.8%
 
2.70659995120.8%
 
3.51132011420.8%
 
3.14884996420.8%
 
3.44308996220.8%
 
2.81183004420.8%
 
2.44666004220.8%
 
3.42657995220.8%
 
2.62701988220.8%
 
3.06579995220.8%
 
2.50143003520.8%
 
2.9531400220.8%
 
2.26263999920.8%
 
3.63509011320.8%
 
4.25171995220.8%
 
2.50071001120.8%
 
2.21030998220.8%
 
2.39209008220.8%
 
2.43616008810.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.11908006710.4%
 
2.21030998220.8%
 
2.26263999920.8%
 
2.26885008810.4%
 
2.28085994710.4%
 
2.3201301110.4%
 
2.32950997420.8%
 
2.33162999220.8%
 
2.33480000510.4%
 
2.3372099420.8%
 
ValueCountFrequency (%) 
5.04877996410.4%
 
4.86814022110.4%
 
4.65980005310.4%
 
4.56224012410.4%
 
4.5245199210.4%
 
4.51512002910.4%
 
4.25171995220.8%
 
4.1851601610.4%
 
4.18514013310.4%
 
4.06585979510.4%
 

absorbance_77
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4851444522539774
Minimum2.618520021438598
Maximum5.356110095977783
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:21.970385image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.618520021
5-th percentile2.787038505
Q13.09602499
median3.407570004
Q33.77056253
95-th percentile4.50752728
Maximum5.356110096
Range2.737590075
Interquartile range (IQR)0.6745375395

Descriptive statistics

Standard deviation0.5460757232
Coefficient of variation (CV)0.1566866828
Kurtosis0.7617903691
Mean3.485144452
Median Absolute Deviation (MAD)0.3425949812
Skewness0.9186772685
Sum836.4346685
Variance0.2981986955
2020-08-25T00:01:22.072255image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.43850994120.8%
 
2.87392997720.8%
 
2.72922992720.8%
 
4.52020978920.8%
 
3.01201009820.8%
 
3.86889004720.8%
 
2.80261993420.8%
 
3.53635001220.8%
 
4.04626989420.8%
 
3.38060998920.8%
 
2.79729008720.8%
 
4.21255016320.8%
 
3.71702003520.8%
 
3.08411002220.8%
 
2.93286991120.8%
 
2.62124991420.8%
 
3.16654992120.8%
 
2.72948002820.8%
 
2.83979988120.8%
 
3.1424899120.8%
 
3.89505004920.8%
 
4.23057985320.8%
 
3.1274800320.8%
 
3.52543997820.8%
 
3.18496990210.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.61852002110.4%
 
2.62124991420.8%
 
2.66617989510.4%
 
2.70654988310.4%
 
2.72922992720.8%
 
2.72948002820.8%
 
2.75108003610.4%
 
2.75658011410.4%
 
2.76687002210.4%
 
2.78810000410.4%
 
ValueCountFrequency (%) 
5.35611009610.4%
 
5.33971023610.4%
 
5.15068006510.4%
 
5.11103010210.4%
 
4.94790983210.4%
 
4.90842008610.4%
 
4.73241996810.4%
 
4.66978979110.4%
 
4.65607976910.4%
 
4.59671020510.4%
 

absorbance_54
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.469911245505015
Minimum2.571700096130371
Maximum5.299210071563722
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:22.183547image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.571700096
5-th percentile2.753701031
Q13.092867553
median3.382640004
Q33.745627403
95-th percentile4.485849309
Maximum5.299210072
Range2.727509975
Interquartile range (IQR)0.65275985

Descriptive statistics

Standard deviation0.5319556947
Coefficient of variation (CV)0.1533052741
Kurtosis0.7933574042
Mean3.469911246
Median Absolute Deviation (MAD)0.3144450188
Skewness0.907269042
Sum832.7786989
Variance0.2829768612
2020-08-25T00:01:22.288109image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.19164991420.8%
 
2.96917009420.8%
 
3.82891011220.8%
 
3.64683008220.8%
 
2.75705003720.8%
 
2.66952991520.8%
 
2.9714200520.8%
 
2.69901990920.8%
 
2.75371003220.8%
 
3.14580011420.8%
 
2.68768000620.8%
 
3.50613999420.8%
 
4.02405977220.8%
 
3.36848998120.8%
 
2.99553990420.8%
 
4.66002988820.8%
 
2.88917994520.8%
 
2.82077002520.8%
 
3.40285992620.8%
 
4.19534015720.8%
 
3.13178992320.8%
 
3.49225997920.8%
 
3.81063008320.8%
 
4.14051008220.8%
 
3.22914004310.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.57170009610.4%
 
2.66952991520.8%
 
2.68768000620.8%
 
2.69901990920.8%
 
2.702699910.4%
 
2.72462010410.4%
 
2.7395899310.4%
 
2.74940991410.4%
 
2.75353002510.4%
 
2.75371003220.8%
 
ValueCountFrequency (%) 
5.29921007210.4%
 
5.28188991510.4%
 
5.09113979310.4%
 
5.03277015710.4%
 
4.90452003510.4%
 
4.72253990210.4%
 
4.67718982710.4%
 
4.66002988820.8%
 
4.60570001610.4%
 
4.59082984910.4%
 

absorbance_91
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2085254162549974
Minimum2.355679988861084
Maximum5.144619941711426
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:22.404201image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.355679989
5-th percentile2.494076419
Q12.803192496
median3.109969974
Q33.550982475
95-th percentile4.171465945
Maximum5.144619942
Range2.788939953
Interquartile range (IQR)0.747789979

Descriptive statistics

Standard deviation0.5480163756
Coefficient of variation (CV)0.1708000731
Kurtosis0.5844005624
Mean3.208525416
Median Absolute Deviation (MAD)0.3584200144
Skewness0.8655772925
Sum770.0460999
Variance0.300321948
2020-08-25T00:01:22.511446image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2.7769200820.8%
 
2.48944997820.8%
 
3.6798698920.8%
 
3.62403988820.8%
 
2.35567998920.8%
 
2.72234010720.8%
 
3.99917006520.8%
 
2.65457010320.8%
 
3.33960008620.8%
 
3.07715988220.8%
 
2.52269005820.8%
 
3.81086993220.8%
 
3.1490299720.8%
 
2.58260989220.8%
 
3.97422003720.8%
 
2.88349008620.8%
 
3.19998002120.8%
 
4.12447977120.8%
 
2.55668997820.8%
 
3.50878000320.8%
 
2.52357006120.8%
 
2.83797001820.8%
 
2.45506000520.8%
 
2.84565997120.8%
 
3.82506990410.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.35567998920.8%
 
2.35880994810.4%
 
2.36396002810.4%
 
2.44485998210.4%
 
2.44799995410.4%
 
2.45506000520.8%
 
2.46515989310.4%
 
2.47534990310.4%
 
2.48944997820.8%
 
2.49431991610.4%
 
ValueCountFrequency (%) 
5.14461994210.4%
 
5.05386018810.4%
 
4.7312798510.4%
 
4.71064996710.4%
 
4.67363977410.4%
 
4.58079004310.4%
 
4.53613996510.4%
 
4.47691011410.4%
 
4.36744022410.4%
 
4.35175991110.4%
 

absorbance_57
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count215
Unique (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.576310459772746
Minimum2.6743500232696533
Maximum5.411829948425293
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:22.624609image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.674350023
5-th percentile2.86432004
Q13.193055034
median3.502510071
Q33.860144913
95-th percentile4.611752534
Maximum5.411829948
Range2.737479925
Interquartile range (IQR)0.6670898795

Descriptive statistics

Standard deviation0.5388887145
Coefficient of variation (CV)0.1506828673
Kurtosis0.8455228954
Mean3.57631046
Median Absolute Deviation (MAD)0.3189001083
Skewness0.9272523171
Sum858.3145103
Variance0.2904010466
2020-08-25T00:01:22.727120image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.51727008820.8%
 
4.26129007320.8%
 
3.21870994620.8%
 
4.11272001320.8%
 
4.28996992120.8%
 
3.75847005820.8%
 
3.05142998720.8%
 
2.79320001620.8%
 
3.28149008820.8%
 
4.75613021920.8%
 
3.92226004620.8%
 
3.61553001420.8%
 
3.2531620.8%
 
2.92038011620.8%
 
3.50251007120.8%
 
3.0849199320.8%
 
3.00072002420.8%
 
3.57161998720.8%
 
2.86914992320.8%
 
2.79485011120.8%
 
3.11898994420.8%
 
3.92183995220.8%
 
2.8643200420.8%
 
3.18360996220.8%
 
2.74988007520.8%
 
Other values (190)19079.2%
 
ValueCountFrequency (%) 
2.67435002310.4%
 
2.74988007520.8%
 
2.79257988910.4%
 
2.79320001620.8%
 
2.79485011120.8%
 
2.81329011910.4%
 
2.85204005210.4%
 
2.8618400110.4%
 
2.8643200420.8%
 
2.86550998710.4%
 
ValueCountFrequency (%) 
5.41182994810.4%
 
5.40620994610.4%
 
5.23696994810.4%
 
5.236380110.4%
 
5.02287006410.4%
 
4.91971015910.4%
 
4.77359008810.4%
 
4.75613021920.8%
 
4.73970985410.4%
 
4.68338012710.4%
 

moisture
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count141
Unique (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.84537490208944
Minimum32.799999237060554
Maximum76.5999984741211
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:22.843352image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum32.79999924
5-th percentile40.98500004
Q155.5
median66.19999695
Q372.02499962
95-th percentile74.30000305
Maximum76.59999847
Range43.79999924
Interquartile range (IQR)16.52499962

Descriptive statistics

Standard deviation11.03780735
Coefficient of variation (CV)0.1756343624
Kurtosis0.01899853359
Mean62.8453749
Median Absolute Deviation (MAD)6.499998093
Skewness-0.9728012485
Sum15082.88998
Variance121.8331911
2020-08-25T00:01:22.936321image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
72.583.3%
 
50.2999992452.1%
 
73.552.1%
 
61.4000015341.7%
 
72.6999969541.7%
 
69.3000030541.7%
 
74.5999984731.2%
 
65.1999969531.2%
 
72.8000030531.2%
 
65.6999969531.2%
 
71.5999984731.2%
 
64.5999984731.2%
 
69.531.2%
 
55.531.2%
 
72.5999984731.2%
 
63.5999984731.2%
 
49.531.2%
 
67.3000030531.2%
 
73.4000015331.2%
 
66.1999969531.2%
 
70.3000030531.2%
 
72.0999984731.2%
 
76.5999984720.8%
 
58.2999992420.8%
 
74.3000030520.8%
 
Other values (116)15665.0%
 
ValueCountFrequency (%) 
32.7999992410.4%
 
32.9000015310.4%
 
3310.4%
 
34.0499992420.8%
 
34.9000015310.4%
 
35.510.4%
 
35.9399986310.4%
 
39.2999992410.4%
 
39.510.4%
 
40.2000007610.4%
 
ValueCountFrequency (%) 
76.5999984720.8%
 
76.0999984710.4%
 
75.5999984720.8%
 
75.0999984710.4%
 
74.5999984731.2%
 
74.520.8%
 
74.3000030520.8%
 
74.1999969510.4%
 
74.0999984720.8%
 
7420.8%
 

principal_component_22
Real number (ℝ)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.025066189945694834
Minimum-1.7170699834823608
Maximum3.647140026092529
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:23.037428image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.717069983
5-th percentile-1.409648556
Q1-0.698264733
median-0.1654189974
Q30.5832222551
95-th percentile1.888599968
Maximum3.647140026
Range5.36421001
Interquartile range (IQR)1.281486988

Descriptive statistics

Standard deviation1.021316934
Coefficient of variation (CV)40.74480152
Kurtosis0.6351282575
Mean0.02506618995
Median Absolute Deviation (MAD)0.6353870183
Skewness0.844508343
Sum6.015885587
Variance1.04308828
2020-08-25T00:01:23.295493image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.967900991420.8%
 
-0.596517026420.8%
 
0.168596997920.8%
 
-0.518966972820.8%
 
-1.48246002220.8%
 
-0.90814900420.8%
 
1.5192899720.8%
 
0.781382024320.8%
 
0.816258013220.8%
 
-1.07060003320.8%
 
-0.938153028520.8%
 
1.38638997120.8%
 
-0.167309999520.8%
 
1.11387002520.8%
 
-1.41171002420.8%
 
-1.53068995520.8%
 
-0.619625985620.8%
 
-1.20755994320.8%
 
2.20022988320.8%
 
0.46617820.8%
 
-1.34617996220.8%
 
-1.41746997820.8%
 
0.0804120004220.8%
 
-0.119571998720.8%
 
0.950012981910.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
-1.71706998310.4%
 
-1.53068995520.8%
 
-1.48246002220.8%
 
-1.44515001810.4%
 
-1.42225003210.4%
 
-1.41928005210.4%
 
-1.41746997820.8%
 
-1.41171002420.8%
 
-1.40954005710.4%
 
-1.37021005210.4%
 
ValueCountFrequency (%) 
3.64714002610.4%
 
3.45159006110.4%
 
2.94218993210.4%
 
2.93931007410.4%
 
2.60577988610.4%
 
2.49043989210.4%
 
2.25939011610.4%
 
2.20022988320.8%
 
2.19619989410.4%
 
2.15916991210.4%
 

absorbance_5
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.830278420448303
Minimum2.064169883728028
Maximum4.278470039367677
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:23.405453image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.064169884
5-th percentile2.233700037
Q12.528457463
median2.762040019
Q33.054682434
95-th percentile3.613693559
Maximum4.278470039
Range2.214300156
Interquartile range (IQR)0.5262249708

Descriptive statistics

Standard deviation0.4223033892
Coefficient of variation (CV)0.149209133
Kurtosis0.6179594537
Mean2.83027842
Median Absolute Deviation (MAD)0.2582999468
Skewness0.8015680429
Sum679.2668209
Variance0.1783401525
2020-08-25T00:01:23.506257image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.51171994220.8%
 
2.6051099320.8%
 
2.19119000420.8%
 
3.16774010720.8%
 
2.91848993320.8%
 
2.89913010620.8%
 
2.39184999520.8%
 
2.51100993220.8%
 
2.23370003720.8%
 
2.15300011620.8%
 
2.46751999920.8%
 
2.68399000220.8%
 
2.22891998320.8%
 
2.6771199720.8%
 
2.28864002220.8%
 
3.11761999120.8%
 
2.39977002120.8%
 
2.91074991220.8%
 
2.63845992120.8%
 
2.74391007420.8%
 
3.8930900120.8%
 
3.35040998520.8%
 
3.38575005520.8%
 
2.24028992720.8%
 
4.27847003910.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.06416988410.4%
 
2.15300011620.8%
 
2.18129992510.4%
 
2.19119000420.8%
 
2.19215011610.4%
 
2.22472000110.4%
 
2.22891998320.8%
 
2.23061990710.4%
 
2.23370003720.8%
 
2.24028992720.8%
 
ValueCountFrequency (%) 
4.27847003910.4%
 
4.25643014910.4%
 
4.11636018810.4%
 
3.96450996410.4%
 
3.8930900120.8%
 
3.78720998810.4%
 
3.73422002810.4%
 
3.68262004910.4%
 
3.68145990410.4%
 
3.66153001810.4%
 

absorbance_28
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.97397679289182
Minimum2.090840101242065
Maximum4.725110054016113
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:23.618723image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.090840101
5-th percentile2.288313544
Q12.610839963
median2.886895061
Q33.264217556
95-th percentile3.863896024
Maximum4.725110054
Range2.634269953
Interquartile range (IQR)0.6533775926

Descriptive statistics

Standard deviation0.494918714
Coefficient of variation (CV)0.1664164681
Kurtosis0.5928869395
Mean2.973976793
Median Absolute Deviation (MAD)0.3102599382
Skewness0.7870728445
Sum713.7544303
Variance0.2449445334
2020-08-25T00:01:23.719503image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.74218988420.8%
 
4.12903976420.8%
 
3.00855994220.8%
 
2.76438999220.8%
 
2.81416988420.8%
 
2.66168999720.8%
 
2.18122005520.8%
 
2.71922993720.8%
 
2.38701009820.8%
 
2.42687010820.8%
 
2.22831010820.8%
 
3.60140991220.8%
 
3.34261989620.8%
 
2.5831000820.8%
 
3.36618995720.8%
 
2.34629988720.8%
 
3.16739988320.8%
 
2.89652991320.8%
 
2.28848004320.8%
 
3.0858520.8%
 
2.28010010720.8%
 
2.29339003620.8%
 
2.44811010420.8%
 
3.56950998320.8%
 
3.86610007310.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.09084010110.4%
 
2.18122005520.8%
 
2.22061991710.4%
 
2.22820997210.4%
 
2.22831010820.8%
 
2.25822997110.4%
 
2.28010010720.8%
 
2.28193998310.4%
 
2.28515005110.4%
 
2.28848004320.8%
 
ValueCountFrequency (%) 
4.72511005410.4%
 
4.62942981710.4%
 
4.40491008810.4%
 
4.35083007810.4%
 
4.1932802210.4%
 
4.1683697710.4%
 
4.12903976420.8%
 
3.96433997210.4%
 
3.95029997810.4%
 
3.94256997110.4%
 

principal_component_2
Real number (ℝ)

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05138024978417282
Minimum-4.464059829711914
Maximum2.7265100479125977
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:23.831809image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-4.46405983
5-th percentile-1.225460052
Q1-0.5495232642
median0.05482154898
Q30.6838707477
95-th percentile1.388145518
Maximum2.726510048
Range7.190569878
Interquartile range (IQR)1.233394012

Descriptive statistics

Standard deviation0.9739102628
Coefficient of variation (CV)18.95495384
Kurtosis3.886619525
Mean0.05138024978
Median Absolute Deviation (MAD)0.6115694363
Skewness-0.8369186135
Sum12.33125995
Variance0.9485012
2020-08-25T00:01:23.951562image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.388303995120.8%
 
-0.0854711011120.8%
 
0.975032985220.8%
 
-1.22546005220.8%
 
1.53576004520.8%
 
1.0525000120.8%
 
-0.642153024720.8%
 
-0.359293997320.8%
 
-0.502550005920.8%
 
0.222213000120.8%
 
-1.48285996920.8%
 
0.507775008720.8%
 
0.293529003920.8%
 
-0.191457003420.8%
 
-1.04881000520.8%
 
-0.548501014720.8%
 
0.75777602220.8%
 
2.52548003220.8%
 
0.156489998120.8%
 
0.191567003720.8%
 
-1.06028997920.8%
 
-0.583862006720.8%
 
0.754386007820.8%
 
1.18333005920.8%
 
-0.603685975110.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
-4.4640598310.4%
 
-4.26314020210.4%
 
-4.21556997310.4%
 
-1.92955005210.4%
 
-1.5922800310.4%
 
-1.51565003410.4%
 
-1.48285996920.8%
 
-1.43619000910.4%
 
-1.34906005910.4%
 
-1.26301002510.4%
 
ValueCountFrequency (%) 
2.72651004810.4%
 
2.62588000310.4%
 
2.52548003220.8%
 
1.57404005510.4%
 
1.53576004520.8%
 
1.52890002710.4%
 
1.47993004310.4%
 
1.40391004110.4%
 
1.39988994610.4%
 
1.39414000510.4%
 

absorbance_45
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.198417503635089
Minimum2.2430799007415767
Maximum5.153240203857422
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:24.081100image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.243079901
5-th percentile2.448774481
Q12.805739939
median3.093950033
Q33.551257491
95-th percentile4.204218554
Maximum5.153240204
Range2.910160303
Interquartile range (IQR)0.7455175519

Descriptive statistics

Standard deviation0.5442494805
Coefficient of variation (CV)0.1701621129
Kurtosis0.6616453542
Mean3.198417504
Median Absolute Deviation (MAD)0.3455450535
Skewness0.8154577584
Sum767.6202009
Variance0.296207497
2020-08-25T00:01:24.187236image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2.91795992920.8%
 
2.39830994620.8%
 
3.56512999520.8%
 
3.90789008120.8%
 
2.86486005820.8%
 
2.63444995920.8%
 
3.18688988720.8%
 
2.34155011220.8%
 
3.14404010820.8%
 
2.44993996620.8%
 
3.25478005420.8%
 
2.57439994820.8%
 
2.43651008620.8%
 
3.99094009420.8%
 
2.72479009620.8%
 
2.51185989420.8%
 
2.82678008120.8%
 
3.07902002320.8%
 
3.5088300720.8%
 
3.63129997320.8%
 
2.63818001720.8%
 
3.75323009520.8%
 
2.42371988320.8%
 
4.38305997820.8%
 
2.96922993710.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.24307990110.4%
 
2.34155011220.8%
 
2.39830994620.8%
 
2.40488004710.4%
 
2.41036009810.4%
 
2.42346000710.4%
 
2.42371988320.8%
 
2.43651008620.8%
 
2.44941997510.4%
 
2.44993996620.8%
 
ValueCountFrequency (%) 
5.15324020410.4%
 
5.0214700710.4%
 
4.75029993110.4%
 
4.74295997610.4%
 
4.58819007910.4%
 
4.57524013510.4%
 
4.44832992610.4%
 
4.38305997820.8%
 
4.32803010910.4%
 
4.23260021210.4%
 

absorbance_96
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.111090126633644
Minimum2.260580062866211
Maximum5.058949947357178
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:24.304340image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.260580063
5-th percentile2.409699917
Q12.703512549
median3.019659996
Q33.469204962
95-th percentile4.057581615
Maximum5.058949947
Range2.798369884
Interquartile range (IQR)0.7656924129

Descriptive statistics

Standard deviation0.5479432617
Coefficient of variation (CV)0.1761258078
Kurtosis0.5318139954
Mean3.111090127
Median Absolute Deviation (MAD)0.3616300821
Skewness0.8504095041
Sum746.6616304
Variance0.3002418181
2020-08-25T00:01:24.407539image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.60473990420.8%
 
2.78534007120.8%
 
2.62491989120.8%
 
2.42634010320.8%
 
2.40969991720.8%
 
3.72715997720.8%
 
3.9875500220.8%
 
2.44895005220.8%
 
3.53314995820.8%
 
3.88546991320.8%
 
2.35907006320.8%
 
2.56124997120.8%
 
2.42560005220.8%
 
3.08183002520.8%
 
3.42949008920.8%
 
3.91462993620.8%
 
2.66794991520.8%
 
3.05159997920.8%
 
3.26946997620.8%
 
2.26462006620.8%
 
2.97357010820.8%
 
2.49429011320.8%
 
2.73230004320.8%
 
2.74360990520.8%
 
3.06348991410.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.26058006310.4%
 
2.26462006620.8%
 
2.26730990410.4%
 
2.34009003610.4%
 
2.35759997410.4%
 
2.35907006320.8%
 
2.36568999310.4%
 
2.36899995810.4%
 
2.40427994710.4%
 
2.40969991720.8%
 
ValueCountFrequency (%) 
5.05894994710.4%
 
4.9453501710.4%
 
4.61584997210.4%
 
4.59795999510.4%
 
4.51911020310.4%
 
4.50319004110.4%
 
4.47567987410.4%
 
4.31737995110.4%
 
4.26667976410.4%
 
4.26231002810.4%
 

absorbance_20
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.90839337905248
Minimum2.0727701187133794
Maximum4.528039932250977
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:24.517442image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.072770119
5-th percentile2.260573077
Q12.571252584
median2.82368505
Q33.175560057
95-th percentile3.764445043
Maximum4.528039932
Range2.455269814
Interquartile range (IQR)0.6043074727

Descriptive statistics

Standard deviation0.4662879613
Coefficient of variation (CV)0.1603249288
Kurtosis0.5640096423
Mean2.908393379
Median Absolute Deviation (MAD)0.2921750546
Skewness0.7870489725
Sum698.014411
Variance0.2174244629
2020-08-25T00:01:24.618130image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2.72849988920.8%
 
2.26347994820.8%
 
3.5061299820.8%
 
2.25162005420.8%
 
3.49254989620.8%
 
2.37264990820.8%
 
2.68513989420.8%
 
2.63329005220.8%
 
3.23877000820.8%
 
3.29633998920.8%
 
4.03238010420.8%
 
2.54858994520.8%
 
2.16250991820.8%
 
2.31709003420.8%
 
2.43626999920.8%
 
2.74480009120.8%
 
2.39558005320.8%
 
2.26059007620.8%
 
2.96577000620.8%
 
3.03799009320.8%
 
2.82203006720.8%
 
2.20599007620.8%
 
3.02726006520.8%
 
3.6448900720.8%
 
2.73070001610.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.07277011910.4%
 
2.16250991820.8%
 
2.19491004910.4%
 
2.20339989710.4%
 
2.20599007620.8%
 
2.22791004210.4%
 
2.25162005420.8%
 
2.25510001210.4%
 
2.26025009210.4%
 
2.26059007620.8%
 
ValueCountFrequency (%) 
4.52803993210.4%
 
4.47157001510.4%
 
4.28657007210.4%
 
4.17299985910.4%
 
4.03238010420.8%
 
4.01117992410.4%
 
3.96763992310.4%
 
3.84771990810.4%
 
3.8305900110.4%
 
3.82947993310.4%
 

absorbance_78
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4674241811037065
Minimum2.6022698879241943
Maximum5.342740058898926
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:24.729120image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.602269888
5-th percentile2.766491556
Q13.075847566
median3.387539983
Q33.755847514
95-th percentile4.491071582
Maximum5.342740059
Range2.740470171
Interquartile range (IQR)0.6799999475

Descriptive statistics

Standard deviation0.5461830395
Coefficient of variation (CV)0.1575183799
Kurtosis0.7495106188
Mean3.467424181
Median Absolute Deviation (MAD)0.3425600529
Skewness0.9150957985
Sum832.1818035
Variance0.2983159126
2020-08-25T00:01:24.835232image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
4.03122997320.8%
 
3.88128995920.8%
 
3.50542998320.8%
 
2.91522002220.8%
 
2.99357008920.8%
 
2.71228003520.8%
 
2.8528499620.8%
 
3.70437002220.8%
 
3.36062002220.8%
 
3.06563997320.8%
 
4.19749021520.8%
 
3.14842009520.8%
 
2.82325005520.8%
 
3.12265992220.8%
 
2.60369992320.8%
 
4.49376010920.8%
 
2.71357011820.8%
 
2.77976989720.8%
 
3.52394008620.8%
 
4.21576023120.8%
 
3.11003994920.8%
 
3.41952991520.8%
 
2.78518009220.8%
 
3.85339999220.8%
 
3.52322006210.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.60226988810.4%
 
2.60369992320.8%
 
2.64630007710.4%
 
2.69010996810.4%
 
2.71228003520.8%
 
2.71357011820.8%
 
2.73082995410.4%
 
2.73721003510.4%
 
2.74885010710.4%
 
2.76742005310.4%
 
ValueCountFrequency (%) 
5.34274005910.4%
 
5.32278013210.4%
 
5.12180995910.4%
 
5.08557987210.4%
 
4.93284988410.4%
 
4.88341999110.4%
 
4.72354984310.4%
 
4.66229009610.4%
 
4.63775014910.4%
 
4.58119010910.4%
 

absorbance_11
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.851989742120107
Minimum2.0634698867797847
Maximum4.353300094604491
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:24.946746image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.063469887
5-th percentile2.239120007
Q12.538077533
median2.776279926
Q33.091012418
95-th percentile3.671506917
Maximum4.353300095
Range2.289830208
Interquartile range (IQR)0.552934885

Descriptive statistics

Standard deviation0.438211676
Coefficient of variation (CV)0.1536512104
Kurtosis0.5726662126
Mean2.851989742
Median Absolute Deviation (MAD)0.2746150494
Skewness0.7957162107
Sum684.4775381
Variance0.192029473
2020-08-25T00:01:25.044840image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2.24273991620.8%
 
2.75991988220.8%
 
2.61147999820.8%
 
2.52102994920.8%
 
3.43413996720.8%
 
2.44548010820.8%
 
2.15265011820.8%
 
2.19249010120.8%
 
3.21913003920.8%
 
2.65346002620.8%
 
2.23401999520.8%
 
2.37929010420.8%
 
2.23912000720.8%
 
3.94063997320.8%
 
2.92695999120.8%
 
3.15319991120.8%
 
2.68952989620.8%
 
3.55644011520.8%
 
2.38109993920.8%
 
3.39638996120.8%
 
2.92671990420.8%
 
2.69729995720.8%
 
2.96199011820.8%
 
2.29503989220.8%
 
2.46773004510.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
2.06346988710.4%
 
2.15265011820.8%
 
2.18033003810.4%
 
2.18973994310.4%
 
2.19249010120.8%
 
2.21428990410.4%
 
2.23380994810.4%
 
2.23401999520.8%
 
2.23912000720.8%
 
2.24273991620.8%
 
ValueCountFrequency (%) 
4.35330009510.4%
 
4.32660007510.4%
 
4.1755399710.4%
 
4.02156019210.4%
 
3.94063997320.8%
 
3.8518700610.4%
 
3.79761004410.4%
 
3.74622988710.4%
 
3.71725988410.4%
 
3.70960998510.4%
 

principal_component_1
Real number (ℝ)

HIGH CORRELATION

Distinct count216
Unique (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02620146224702087
Minimum-1.7071700096130369
Maximum3.6231300830841056
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:25.148817image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.70717001
5-th percentile-1.386414969
Q1-0.6980747432
median-0.1695729941
Q30.5814020038
95-th percentile1.915250546
Maximum3.623130083
Range5.330300093
Interquartile range (IQR)1.279476747

Descriptive statistics

Standard deviation1.023758004
Coefficient of variation (CV)39.0725523
Kurtosis0.6478474144
Mean0.02620146225
Median Absolute Deviation (MAD)0.6370964944
Skewness0.8548177114
Sum6.288350939
Variance1.048080451
2020-08-25T00:01:25.253579image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.15734994420.8%
 
-1.50734996820.8%
 
1.50287997720.8%
 
1.38742995320.8%
 
0.769445002120.8%
 
0.465301990520.8%
 
-0.169572994120.8%
 
-0.944242000620.8%
 
-0.145483002120.8%
 
0.80556297320.8%
 
-1.40413999620.8%
 
-1.08258998420.8%
 
-0.913836002320.8%
 
0.175044000120.8%
 
-1.38859999220.8%
 
-0.600076019820.8%
 
-0.973287999620.8%
 
2.18017005920.8%
 
-1.23020005220.8%
 
-0.596816003320.8%
 
-1.50686001820.8%
 
-1.33752000320.8%
 
0.0789036974320.8%
 
-0.528840005420.8%
 
-0.652996003610.4%
 
Other values (191)19179.6%
 
ValueCountFrequency (%) 
-1.7071700110.4%
 
-1.50734996820.8%
 
-1.50686001820.8%
 
-1.44939005410.4%
 
-1.43032002410.4%
 
-1.41023004110.4%
 
-1.40413999620.8%
 
-1.38859999220.8%
 
-1.38629996810.4%
 
-1.34880995810.4%
 
ValueCountFrequency (%) 
3.62313008310.4%
 
3.49726009410.4%
 
3.03643989610.4%
 
2.84964990610.4%
 
2.65387010610.4%
 
2.49339008310.4%
 
2.3976399910.4%
 
2.19406008710.4%
 
2.18017005920.8%
 
2.17263007210.4%
 

absorbance_12
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count215
Unique (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8565737058719
Minimum2.0638699531555176
Maximum4.368110179901123
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:25.363364image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.063869953
5-th percentile2.241219997
Q12.540657461
median2.780689955
Q33.098787427
95-th percentile3.681327403
Maximum4.36811018
Range2.304240227
Interquartile range (IQR)0.5581299663

Descriptive statistics

Standard deviation0.4409819294
Coefficient of variation (CV)0.1543744271
Kurtosis0.5681664755
Mean2.856573706
Median Absolute Deviation (MAD)0.2761849165
Skewness0.7948403608
Sum685.5776894
Variance0.1944650621
2020-08-25T00:01:25.461405image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2.38059997620.8%
 
3.16037011120.8%
 
2.29668998720.8%
 
2.15304994620.8%
 
3.94956994120.8%
 
2.44292998320.8%
 
2.61312007920.8%
 
2.96915006620.8%
 
2.76414990420.8%
 
3.40499997120.8%
 
3.56464004520.8%
 
2.7898600120.8%
 
3.44215011620.8%
 
2.65639996520.8%
 
2.24380993820.8%
 
2.9339299220.8%
 
2.2347700620.8%
 
3.22759008420.8%
 
2.24121999720.8%
 
2.52330994620.8%
 
2.69300007820.8%
 
2.19320988720.8%
 
2.37702989620.8%
 
2.93028998420.8%
 
2.70005989120.8%
 
Other values (190)19079.2%
 
ValueCountFrequency (%) 
2.06386995310.4%
 
2.15304994620.8%
 
2.1809101110.4%
 
2.19007992710.4%
 
2.19320988720.8%
 
2.2137401110.4%
 
2.2347700620.8%
 
2.23503994910.4%
 
2.24121999720.8%
 
2.24380993820.8%
 
ValueCountFrequency (%) 
4.3681101810.4%
 
4.33977985410.4%
 
4.18645000510.4%
 
4.03351020810.4%
 
3.94956994120.8%
 
3.86482000410.4%
 
3.81088995910.4%
 
3.75712990810.4%
 
3.72547006610.4%
 
3.72016000710.4%
 

target
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count157
Unique (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.502083312968413
Minimum0.8999999761581421
Maximum58.5
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:01:25.568826image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0.8999999762
5-th percentile3.594999909
Q17.074999928
median13.5
Q328.32499933
95-th percentile47.79999924
Maximum58.5
Range57.60000002
Interquartile range (IQR)21.2499994

Descriptive statistics

Standard deviation14.36250499
Coefficient of variation (CV)0.7762642046
Kurtosis0.08816751834
Mean18.50208331
Median Absolute Deviation (MAD)7.549999952
Skewness1.003501925
Sum4440.499995
Variance206.2815495
2020-08-25T00:01:25.679189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
6.40000009562.5%
 
6.80000019141.7%
 
7.19999980941.7%
 
10.1000003841.7%
 
6.59999990541.7%
 
1141.7%
 
5.59999990541.7%
 
11.1999998141.7%
 
7.69999980941.7%
 
7.09999990531.2%
 
3.70000004831.2%
 
35.2000007631.2%
 
5.19999980931.2%
 
631.2%
 
16.3999996231.2%
 
31.531.2%
 
13.531.2%
 
3.90000009520.8%
 
14.6000003820.8%
 
18.7999992420.8%
 
13.8000001920.8%
 
8.39999961920.8%
 
4.59999990520.8%
 
28.8999996220.8%
 
2.90000009520.8%
 
Other values (132)16267.5%
 
ValueCountFrequency (%) 
0.899999976220.8%
 
1.39999997610.4%
 
1.70000004820.8%
 
220.8%
 
2.79999995220.8%
 
2.90000009520.8%
 
3.510.4%
 
3.59999990510.4%
 
3.70000004831.2%
 
3.90000009520.8%
 
ValueCountFrequency (%) 
58.510.4%
 
57.9000015310.4%
 
56.5999984710.4%
 
56.1300010720.8%
 
55.0999984720.8%
 
54.7400016810.4%
 
49.0999984710.4%
 
48.510.4%
 
48.2000007610.4%
 
47.7999992420.8%
 

Interactions

2020-08-25T00:00:28.143228image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:28.270631image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:28.397180image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:28.534396image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:28.823945image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:28.953047image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.077775image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.203419image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.318180image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.443458image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.567038image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.689897image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.820250image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:29.953485image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.079239image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.203596image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.327666image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.455971image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.576743image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.699671image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.827342image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:30.955530image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.080676image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.209261image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.332547image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.459273image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.587140image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.712425image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.827081image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:31.947062image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:32.070922image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:32.196730image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:32.328495image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:32.455168image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:32.767515image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:32.910180image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.037292image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.158349image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.278979image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.401361image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.539756image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.670788image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.806606image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:33.942842image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.076825image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.207707image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.339453image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.471728image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.593819image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.718874image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.842733image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:34.971645image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:35.112225image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:35.240882image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:35.370036image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:35.503347image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:35.637878image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:35.766092image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:35.892503image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:36.023302image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:36.158206image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:36.281279image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:36.404008image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:36.703743image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:36.826057image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:36.948487image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.089868image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.212511image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.327245image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.445775image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.566633image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.688896image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.819919image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:37.951096image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.078422image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.202297image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.325184image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.446124image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.567758image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.687679image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.814412image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:38.939175image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.063814image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.193316image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.318136image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.442077image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.567771image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.692490image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.806544image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:39.925985image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:40.047827image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:00:40.176017image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
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2020-08-25T00:01:07.356228image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:07.481689image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:07.606198image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:07.728442image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:07.854342image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:08.159450image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:08.283149image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:08.407515image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:08.533432image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:08.649685image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:08.769973image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:08.891069image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.016894image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.152868image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.275938image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.403300image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.531094image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.655890image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.776182image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:09.898257image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.017829image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.148283image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.266836image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.390218image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.534324image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.659401image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.779415image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:10.901115image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:11.023922image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:11.137686image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:11.252821image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:11.366055image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:11.483552image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:11.610614image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:11.730048image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.022729image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.143757image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.262324image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.378155image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.492419image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.607399image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.728987image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.847365image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:12.964532image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.086509image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.209851image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.326957image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.444888image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.562057image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.673002image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.786307image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:13.903554image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.020587image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.146216image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.264512image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.382527image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.499188image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.619898image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.733626image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.847032image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:14.962399image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:15.091795image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:15.214895image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:15.332632image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:15.458901image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:15.576709image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:15.873325image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:15.990964image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.110099image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.221279image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.336339image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.451694image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.574396image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.700939image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.819360image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:16.938208image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.055994image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.176468image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.296456image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.414327image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.531664image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.652286image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.780650image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:17.908282image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.039722image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.168911image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.297749image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.422744image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.561113image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.679481image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.803222image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:18.926527image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:19.053262image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:19.190052image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:19.315586image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:19.441706image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:19.777535image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:19.903260image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:20.026217image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:20.148678image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:20.284916image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-25T00:01:25.830722image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-25T00:01:26.351741image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-25T00:01:26.711090image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-25T00:01:27.070391image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-25T00:01:20.571486image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:01:21.085147image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

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02.665852.920852.827063.278913.217713.002473.3284760.500000-0.4193132.619812.72628-0.4586342.938462.899662.672813.262322.62964-0.4303002.6324522.500000
12.949293.306813.215843.476263.431883.304733.5145846.0000000.0966922.851383.053450.6202973.297003.240452.960723.465522.882640.1052432.8889840.099998
22.633612.806492.733442.995693.085542.709343.1667771.000000-0.7102902.589962.678921.3272402.835412.614612.638352.976122.60414-0.7461642.607148.400000
32.873083.045792.971593.333763.347932.998203.4599872.800003-0.1659632.830012.920431.0173603.078892.879882.877893.312042.84374-0.1993372.846645.900000
42.863313.201403.081533.613053.498003.322013.6478958.2999990.1457772.795382.94986-1.2080903.225443.217652.872803.594632.812720.1238632.8170425.500000
53.144573.556993.439743.739293.658303.571633.7580344.0000000.6043823.031903.263930.3899253.556563.509723.157033.728313.069820.5764823.0772442.700001
63.135663.516193.445113.672293.682623.505443.7494744.0000000.5564103.011173.258120.7697903.502593.444563.149363.661753.052130.5106503.0603242.700001
72.568082.775162.682883.184973.126832.889033.2532269.300003-0.6072872.529442.61666-0.7349882.810832.783722.573283.166232.53937-0.6337462.5419310.600000
83.414913.743533.634424.149584.068623.849164.2018361.4000021.2373403.299563.51296-0.3613103.771843.737093.425864.130863.342431.1968103.3503519.900000
93.555453.910293.796704.305354.295693.981734.4059261.4000021.4973803.427353.66176-0.2667593.940033.864133.567574.285333.475111.5088403.4838519.900000

Last rows

absorbance_19absorbance_43absorbance_37absorbance_77absorbance_54absorbance_91absorbance_57moistureprincipal_component_22absorbance_5absorbance_28principal_component_2absorbance_45absorbance_96absorbance_20absorbance_78absorbance_11principal_component_1absorbance_12target
2302.260052.393842.329512.621252.669532.355682.7498873.500000-1.4824602.228922.293390.7577762.423722.264622.263482.603702.23912-1.5073502.241223.7
2312.383692.532202.463372.756582.820842.465162.9052473.300003-1.2261602.348902.421950.8906792.563612.365692.387592.737212.35996-1.2472802.362373.9
2322.731872.896632.821893.219573.208352.946153.2990873.199997-0.4590452.678812.776190.4687072.930382.847452.736773.202612.69884-0.4494162.702554.4
2332.734922.903342.822893.186253.242472.854333.3386273.000000-0.4680472.697942.776290.8445152.939922.738832.739273.164712.70918-0.4751192.711704.6
2343.063813.253543.172753.573533.579913.244783.6901370.0000000.2285373.010273.116890.8810853.288083.127763.069363.552513.028650.2342813.032346.6
2353.325723.551103.460703.884913.897523.581144.0022370.0000000.8240973.244763.391710.7794913.588733.475993.332953.865113.275920.8252093.281546.6
2363.409273.638303.546493.932923.995433.576224.1014669.6999970.9500133.326833.477001.2657103.676383.452513.416833.909553.357960.9521503.363647.1
2372.721382.907202.826073.228833.238142.937543.3371769.099998-0.4381172.670652.770660.3159962.941452.835032.726703.210112.68813-0.4379392.691577.7
2383.133083.344043.268713.610083.618073.364663.7017366.3000030.3830603.046533.199081.0958703.371933.277773.140473.594233.080820.3628743.0868910.4
2393.463613.757073.650644.167914.115683.877064.2305365.1999971.2299403.352753.55266-0.1335243.792623.771733.473364.149843.396101.2579403.4037812.3

Duplicate rows

Most frequent

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02.160582.297102.210312.729482.687682.455062.7948576.599998-1.5306902.153002.18122-1.0602902.341552.359072.162512.712282.15265-1.5068602.153050.92
12.203512.353172.262642.802622.753712.523572.8643275.599998-1.4174702.191192.22831-1.2254602.398312.425602.205992.785182.19249-1.3886002.193212.02
22.248252.412232.337212.729232.699022.489452.7932061.400002-1.4117102.233702.28010-0.1914572.436512.409702.251622.713572.23402-1.4041402.2347714.62
32.257522.413462.331632.797292.757052.522692.8691572.500000-1.3461802.240292.28848-0.6421532.449942.426342.260592.779772.24274-1.3375202.243816.42
42.260052.393842.329512.621252.669532.355682.7498873.500000-1.4824602.228922.293390.7577762.423722.264622.263482.603702.23912-1.5073502.241223.72
52.313652.475292.392092.839802.820772.582612.9203872.500000-1.2075602.288642.34630-0.5025502.511862.494292.317092.823252.29504-1.2302002.296696.42
62.371802.542572.446662.932872.889182.654573.0007271.300003-1.0706002.399772.38701-0.5485012.574402.561252.372652.915222.37929-1.0825902.3770313.82
72.391752.605872.501433.084112.995542.776923.1189964.599998-0.9081492.391852.42687-1.4828602.638182.667952.395583.065642.38110-0.9138362.3806013.52
82.435712.598132.500713.012012.969172.722343.0849272.900002-0.9381532.467522.44811-0.5838622.634452.624922.436272.993572.44548-0.9442422.4429311.22
92.544652.695032.627022.873932.971422.556693.0514374.500000-0.9679012.511012.583101.5357602.724792.448952.548592.852852.52103-0.9732882.523315.22